Effect of sieved fractionation on the physical,flow and hydration properties of Boscia senegalensis Lam., Dichostachys glomerata Forssk. and Hibiscus sabdariffa L. powders

Food Science and Biotechnology - This study aimed at evaluating the effect of successive grinding and sieving processes on the physicochemical properties of powders obtained from Boscia...     

Alternation drying and grinding (ADG) technique: A novel approach for producing ripe mango powder

The effectiveness of the alternation of drying and grinding of ripe mango for powder production was studied. Mango endosperm was dried to different moisture content and ground. There was no significant difference in ash, pectin, reducing and total sugars, starch, proteins and fat content between undried and dried mango. Bond, Kick and Rittinger grinding constants were determined. X-ray diffraction, scanning electron microscopy, differential scanning calorimetry and infrared analysis of mango granules were carried out before and after drying. Intermittent drying and grinding of ripe mango is recommended in order to increase its grinding ability. Improvement in grinding ability was characterized by the elimination of caking during grinding, the increase of the grinding yield, and the reduction of the final particle size and the energy requirement for grinding. The application of this method to ripe mango resulted in the oxidation of C-OH bonds to CO bonds in the molecular structure.     

Edge detection of intestinal parasites in stool microscopic images using multi-scale wavelet transform

Biomedical image processing is experiencing a significant progress with many applications. However, automatic recognition of microscopic pathogens from their images remains a challenge that will allow clinical laboratories to increase both the speed of tests and the reliability of diagnoses. We present an algorithm for edge detection of parasites in microscopic images of stools, using the multi-scale wavelet transform. This method is an evolution of the Canny–Mallat detector which gives the possibility to vary the frequency of the analysis in order to find the outlines of the most significant edges. The various contours obtained are chained across the scales from the coarsest to the finest. Using this algorithm, we were able to correctly represent the contours of the features of parasites found in microscopic images. The results obtained were compared with those produced by classical edge detectors on the same images. It comes out from both subjective and objective quantitative performances evaluation that our detector, better than all others, can clearly mark the outlines of the structures of the pathogen on an image of stools.